Made changes to Getting started with ALwrity and added lot of details on API keys
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ajaysi
@@ -1,7 +1,35 @@
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import textstat
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import streamlit as st
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"""Text analysis tools using textstat."""
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st.set_page_config(layout="wide", page_title="Text Readability Analyzer", page_icon=":book:")
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import streamlit as st
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from textstat import textstat
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def analyze_text(text):
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"""Analyze text using textstat metrics."""
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if not text:
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st.warning("Please enter some text to analyze.")
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return
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# Calculate various metrics
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metrics = {
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"Flesch Reading Ease": textstat.flesch_reading_ease(text),
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"Flesch-Kincaid Grade Level": textstat.flesch_kincaid_grade(text),
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"Gunning Fog Index": textstat.gunning_fog(text),
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"SMOG Index": textstat.smog_index(text),
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"Automated Readability Index": textstat.automated_readability_index(text),
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"Coleman-Liau Index": textstat.coleman_liau_index(text),
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"Linsear Write Formula": textstat.linsear_write_formula(text),
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"Dale-Chall Readability Score": textstat.dale_chall_readability_score(text),
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"Readability Consensus": textstat.readability_consensus(text)
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}
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# Display metrics in a clean format
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st.subheader("Text Analysis Results")
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for metric, value in metrics.items():
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st.metric(metric, f"{value:.2f}")
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# Add visualizations
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st.subheader("Visualization")
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st.bar_chart(metrics)
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st.title("📖 Text Readability Analyzer: Making Your Content Easy to Read")
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@@ -10,122 +38,6 @@ st.write("""
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Just paste in a sample of your text, and we'll break down the readability scores and offer actionable tips!
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""")
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def analyze_text(test_data):
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"""
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Analyzes the readability of the provided text and returns a dictionary with the results.
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Parameters:
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test_data (str): The text to be analyzed.
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Returns:
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dict: A dictionary containing readability scores and additional metrics.
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"""
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return {
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"Flesch Reading Ease": {
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"score": textstat.flesch_reading_ease(test_data),
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"description": "This score rates your text on a scale of 0-100, with higher scores being easier to read.",
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"tips": [
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"Score below 30? Simplify your text by breaking down complex sentences, using shorter words, and avoiding jargon.",
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"Score around 60-70? You're in the 'standard' range.",
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"Score over 90? Your text is very easy to read. Add some complexity or sophistication if needed."
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]
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},
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"Flesch-Kincaid Grade Level": {
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"score": textstat.flesch_kincaid_grade(test_data),
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"description": "This formula estimates the US school grade level needed to understand your text.",
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"tips": [
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"High Score? Your writing might be too complex for your target audience.",
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"Low Score? Your audience might find the text too simple.",
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"Match Your Audience: Tailor the complexity to your readers."
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]
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},
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"SMOG Index": {
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"score": textstat.smog_index(test_data),
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"description": "This formula measures text complexity by looking at the number of long words and sentences.",
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"tips": [
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"Best for texts with at least 30 sentences.",
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"Adjust complexity to match your target audience."
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]
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},
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"Coleman-Liau Index": {
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"score": textstat.coleman_liau_index(test_data),
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"description": "This formula uses sentence length and the number of syllables per word to estimate the reading level."
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},
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"Automated Readability Index (ARI)": {
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"score": textstat.automated_readability_index(test_data),
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"description": "Estimates the grade level required to comprehend your text."
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},
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"Dale-Chall Readability Score": {
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"score": textstat.dale_chall_readability_score(test_data),
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"description": "Focuses on the number of uncommon words (not on a list of 3000 common words) and sentence length.",
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"tips": [
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"Easy to Understand: Aim for a score around the reading level of your audience.",
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"High School Level? Scores between 9 and 12 indicate a high school reading level.",
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"Beyond High School? Scores above 12 are usually for a college-level audience."
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]
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},
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"Gunning Fog": {
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"score": textstat.gunning_fog(test_data),
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"description": "Calculates the grade level required to understand the text."
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},
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"Linsear Write Formula": {
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"score": textstat.linsear_write_formula(test_data),
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"description": "Estimates the US grade level needed to understand the text."
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},
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"Text Standard (Consensus)": {
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"score": textstat.text_standard(test_data),
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"description": "A consensus estimate of the US grade level needed to understand your text, based on multiple readability scores."
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},
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"Spache Readability": {
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"score": textstat.spache_readability(test_data),
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"description": "Best for analyzing text for children, typically up to grade 4.",
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"tips": [
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"Considers the number of unfamiliar words and the length of sentences."
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]
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},
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"McAlpine EFLAW": {
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"score": textstat.mcalpine_eflaw(test_data),
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"description": "Evaluates text for foreign language learners, focusing on 'miniwords' and sentence length.",
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"tips": [
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"Target Score: Aim for a score of 25 or less."
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]
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},
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"Reading Time": {
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"score": textstat.reading_time(test_data),
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"description": "Estimated reading time in minutes."
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},
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"Syllable Count": {
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"score": textstat.syllable_count(test_data),
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"description": "The number of syllables in the text."
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},
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"Word Count": {
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"score": textstat.lexicon_count(test_data),
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"description": "The number of words in the text."
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},
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"Sentence Count": {
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"score": textstat.sentence_count(test_data),
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"description": "The number of sentences in the text."
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},
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"Character Count": {
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"score": textstat.char_count(test_data),
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"description": "The number of characters in the text."
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},
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"Letter Count (without punctuation)": {
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"score": textstat.letter_count(test_data),
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"description": "The number of letters without punctuation."
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},
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"Polysyllable Count": {
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"score": textstat.polysyllabcount(test_data),
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"description": "The number of polysyllabic words in the text."
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},
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"Monosyllable Count": {
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"score": textstat.monosyllabcount(test_data),
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"description": "The number of monosyllabic words in the text."
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}
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}
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text_input = st.text_area("Paste your text here:", height=200)
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if st.button("Analyze!"):
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@@ -134,18 +46,7 @@ if st.button("Analyze!"):
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if not test_data.strip():
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st.error("Please enter text to analyze.")
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else:
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results = analyze_text(test_data)
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st.subheader("Readability Scores:")
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st.write("---")
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for metric, data in results.items():
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st.markdown(f"**{metric}:** {data['score']}")
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st.markdown(f"* **What It Means:** {data['description']}")
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if 'tips' in data:
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st.markdown("* **Actionable Tips:**")
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for tip in data['tips']:
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st.markdown(f" * {tip}")
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st.write(" ")
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analyze_text(test_data)
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st.subheader("Key Takeaways:")
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st.write("---")
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